Work order automatic processing system and method based on artificial intelligence

Abstract

The invention discloses a work order automatic processing system and method based on artificial intelligence, and relates to the technical field of work order automatic processing, and the method comprises the steps: based on historical data, analyzing the historical processing data of processing personnel, marking the current state of the processing personnel, screening keywords contained in a work order when a processing order is added, and analyzing the adaptability of the processing personnel to the work order. The method comprises the following steps: comprehensively considering the degree of adaptation and the success rate of processing the work order, selecting an executor and a cooperative processing worker for the work order, adjusting the labels of the executor and the cooperative processing worker, and selecting an assistant worker to complete the work order according to work order information. According to the method and the system, matching personnel skilled in processing weak links of execution personnel are matched, so that resource waste caused by random or empirical distribution in the past is avoided, each processing personnel can exert advantages in the most skilled field, and efficient utilization of human resources is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic processing of work orders, in particular to an automatic processing system and method of work orders based on artificial intelligence. BACKGROUND

[0002] In enterprise service and operation management, work order processing is the core link connecting customer demand and service response. The traditional work order processing mode mainly relies on manual allocation, and the work order is distributed to the relevant personnel through experience judgment. This method has obvious disadvantages: manual allocation is easily affected by subjective factors, and it is difficult to accurately match the work order type and the processing personnel's ability, resulting in waste of resources and low processing efficiency; as the business scale expands and the work order type becomes more complex, the limitations of manual processing become more prominent, and the processing personnel may cause work order backlog due to task overload or skill mismatch, affecting customer experience, and the existing technology introduces an automatic allocation system based on rules, which realizes the preliminary screening and distribution of work orders through preset keywords or classification tags. Although this method reduces manual intervention to some extent, it still has obvious shortcomings, and the rules are formulated based on static experience, which is difficult to adapt to dynamic business scenarios; at the same time, the real-time state of the processing personnel is not considered, and key indicators such as idle time and historical processing success rate are difficult to consider, resulting in allocation results that cannot balance efficiency and quality. Some systems attempt to combine machine learning technology for work order classification and personnel matching, but most focus on text semantic analysis and do not fully integrate multi-dimensional data of processing personnel, resulting in one-sidedness of adaptation degree calculation and difficulty in achieving optimal allocation of resources. In complex business scenarios, work order processing often involves multi-link cooperation and dynamic adjustment. When the executor encounters technical bottlenecks in the processing process, the traditional system lacks effective assistance mechanisms and needs manual coordination of resources, further prolonging the processing cycle. SUMMARY

[0003] The present application aims to provide an automatic processing system and method of work orders based on artificial intelligence to solve the problems raised in the background art.

[0004] In order to solve the above technical problems, the present application provides the following technical scheme: an automatic processing method of work orders based on artificial intelligence, comprising the following steps:

[0005] S1, based on historical data, analyzing the historical processing data of the processing personnel to mark the current state of the processing personnel;

[0006] S2, when adding a work order, screening the work order for keywords, and analyzing the adaptation degree of the processing personnel to the work order;

[0007] S3, considering the adaptation degree and the processing success rate of the work order to select the executor and the cooperating personnel for the work order;

[0008] S4. Adjust the labels of the executor and cooperating personnel, and select the assisting personnel to complete the work order based on the work order information.

[0009] Furthermore, in step S1, after authorization, the processing personnel information is collected, and the processing personnel set is {A1, A2, ..., A i ,…,A I}, for processing personnel A i Perform analysis and process personnel A i The number of times the preset X keywords are processed is {B1, B2, ..., B x ,…,B X}, where B x Indicates processing personnel A i Number of times the work order containing the xth keyword was processed by processing person A i The success rate of processing work orders containing the xth keyword is W i_x , and then get the processing personnel A i The comprehensive treatment success rate W i , W i For processing personnel A i For the average processing success rate of the work order, we substitute i=1,2,…,I one by one to get the comprehensive processing success rate of I processing personnel {W1,W2,…,W i ,…,W I}, add a mark to the processing personnel, marked with the idle time of the processing personnel. If the processing personnel is not idle, the idle time will be set to 0; by collecting and analyzing the processing personnel information, we can fully understand the processing capabilities of each personnel for different types of work orders, and clearly grasp their areas of expertise and processing levels. Analyzing the number of processing times and success rates can accurately locate the advantages of personnel, facilitate the optimization of task allocation, and improve the efficiency and success rate of work order processing. Adding idle time marks to processing personnel can intuitively reflect the work status of personnel, facilitate the reasonable arrangement of workload, avoid excessive fatigue or idle resources, and achieve scientific adjustment of personnel work rhythm. This series of operations helps managers to grasp the comprehensive situation of personnel in real time, improve the scientific and targeted management, promote the balanced allocation of personnel resources, enhance team collaboration efficiency, create an efficient and orderly working environment, promote the improvement of overall work efficiency, ensure stable service quality, and provide strong support for the orderly development of business and team development.

[0010] Furthermore, in step S2, when adding a work order, after authorization, the work order information is collected and compared with the preset X keywords to obtain the work order keywords, where the work order keywords represent the keywords contained in the work order, and the work order keywords include {C1, C2, ..., C y ,…,C Y}, where Y represents the number of keywords included in the work order, C yIndicates the yth keyword involved in the work order, and gets the processing person A i The success rate of handling work orders related to the yth keyword D i_y , and then get the processing personnel A i Adaptability to work orders E i :

[0011]

[0012] where k i1 Indicates the keyword weight to be calculated, k i2 Indicates the comprehensive weight to be calculated;

[0013] Consider Processor A i Idle time F i Set keyword weight k i1 , k i1 =f i / f0, where f i For processing personnel A i The effective idle time length, f0 is the maximum effective idle time length, when f i When ≤f0, let f i =F i When f i >f0, let f i =f0, comprehensive weight k i2 =k i1 , and then get the adaptability of I processing personnel to the work order {E1, E2, ..., E i ,…,E IFrom the perspective of precise matching and processing efficiency improvement, the method can ensure that the work order is distributed to the personnel with high processing success rate in the keyword field by collecting work order information and comparing preset keywords, accurately obtaining work order keywords, and combining the processing success rate of the processing personnel for each keyword related work order to calculate the adaptation degree. This enables the processing personnel to quickly take over familiar business, reduces time waste and processing errors caused by unfamiliar business, greatly improves the efficiency and pertinence of work order processing, and enables work orders to be professionally processed in the shortest time. In terms of optimal allocation of processing resources, the actual idle time of the processing personnel is fully considered to set the keyword weight. When the effective idle time of the processing personnel does not exceed the maximum effective idle time, the weight is directly calculated based on the actual idle time; otherwise, the maximum effective idle time is used as the reference. Such design avoids over-reliance on or neglect of a certain processing personnel. By dynamically adjusting the keyword weight, the workload of the processing personnel is balanced, enabling personnel with longer idle time to have more opportunities to undertake work orders, avoiding overloading of busy personnel, achieving reasonable allocation of processing resources, and improving the collaboration efficiency of the overall processing team. From the perspective of processing quality and customer satisfaction, personnel with high processing success rate can process related keyword work orders more professionally and efficiently, improve the quality and accuracy of work order resolution, and reduce rework and error processing. Customers' problems can be quickly and effectively solved, which will inevitably improve customer satisfaction with the service and enhance customers' trust in the system and service team.

[0014] Further, in step S3, the first processing personnel is sorted in descending order of the adaptation degree to the work order, wherein the first processing personnel has the highest adaptation degree to the work order, and the adaptation degree of the first processing personnel to the work order is E p The first processing personnel is taken as the executor of the work order.

[0015] The processing success rate of the first processing personnel to the Y keyword related work orders is {D p_1 ,D p_2 ,…,D p_y ,…,D p_Y}, through historical data, the average processing success rate of the processing personnel to the Y keyword related work orders is {D1,D2,…,D y ,…,D Y}, wherein D y is the average processing success rate of the processing personnel to the y keyword related work order, if D p_y <D y , the y keyword is classified as a processing keyword, and the processing keyword set is {H1,H2,…,H p ,…,H P}, wherein P represents the number of processing keywords, and H prepresents the pth keyword to be processed, a virtual work order is established, the virtual work order contains P keywords to be processed, and the adaptation degrees of I handlers to the virtual work order {e1, e2, …, e i ,…,e I} are obtained, and the handler with the highest adaptation degree to the virtual work order is selected as the cooperative handler;

[0016] The idle time length of the cooperative handler is checked, if the idle time length of the cooperative handler is 0, the cooperative handler is reselected from the non-cooperative handlers until the idle time length of the cooperative handler is not 0;

[0017] The idle time length of the cooperative handler is checked, if the idle time length of the cooperative handler is 0, the cooperative handler is reselected from the non-cooperative handlers until the idle time length of the cooperative handler is not 0;

[0018] The order is sorted according to the adaptation degree to match the main execution personnel, which can ensure that the task is assigned to the personnel who is best at processing this type of work order, maximize the expertise of personnel, and improve the initial efficiency and success rate of work order processing. For the weak keyword field of the main execution personnel, the personnel with the strongest processing ability in this field is selected as the assistant, which can effectively make up for the shortcomings of the main execution personnel, form a complementary cooperative working mode, and further guarantee the overall quality of work order processing. At the same time, by checking the idle time length of the cooperative personnel, the dynamic adjustment of personnel can be avoided, which can avoid the delay or quality decline caused by assigning tasks to busy personnel, ensure that the cooperative personnel has sufficient energy to work, and realize the reasonable allocation of human resources and the scientific balance of task load. This allocation mechanism of main and auxiliary combination and consideration of personnel state can not only improve the processing efficiency of a single work order, but also promote the cooperation between team members, and promote the efficient operation of the overall work process and the stable improvement of service level.

[0019] Further, in step S4, after the selection of the execution personnel and the cooperative handler is completed, the work order information is transmitted to the execution personnel and the cooperative handler, and the idle time length of the execution personnel and the cooperative handler is locked to 0 until the work order is completed. If the execution personnel and the cooperative handler submit a help application during the execution of the work order, the handler with the highest average processing success rate for the work order is selected as the assistant from the handlers with non-zero idle time length, the work order information is transmitted to the assistant, and the assistance instruction is issued;

[0020] After completing the execution and matching personnel selection, the idle duration is locked, which can ensure the concentration of personnel during work order processing, avoid processing interruption caused by task switching or resource occupation, guarantee the continuity and concentration of work order execution, and improve processing efficiency and quality stability. When the help mechanism is triggered during execution, the assistance personnel with the highest average processing success rate is selected from the idle personnel, which can quickly respond to complex problems, solve difficult problems in time with personnel with strong professional ability and ready state, and prevent problems from affecting the overall progress. This combination of locking and dynamic help mechanism not only realizes the scientific management of personnel working state, but also builds a flexible and efficient collaboration network, so that the team can quickly allocate resources when facing tasks of different difficulties, form a multi-level support system, enhance the overall ability to cope with complex work orders, promote experience complementation and cooperation between personnel, create an efficient and cooperative working atmosphere, and promote the smooth operation of business processes and continuous improvement of service efficiency.

[0021] An artificial intelligence-based work order automatic processing system, the system comprising: a processing personnel state analysis module, a work order keyword adaptation analysis module, a processing personnel intelligent selection module, and a work order processing collaboration adjustment module;

[0022] The processing personnel state analysis module is configured to analyze historical processing data of processing personnel based on historical data, and to indicate the current state of the processing personnel.

[0023] The work order keyword adaptation analysis module is configured to filter keywords included in a work order when the work order is added, and to analyze the adaptation degree of the processing personnel to the work order.

[0024] The processing personnel intelligent selection module is configured to consider the adaptation degree and the processing success rate of the processing personnel to the work order, and to select an execution personnel and a cooperative processing personnel for the work order.

[0025] The work order processing collaboration adjustment module is configured to adjust the labels of the execution personnel and the cooperative processing personnel, and to select an assistance personnel to complete the work order according to the work order information.

[0026] Further, the processing personnel state analysis module, the work order keyword adaptation analysis module, the processing personnel intelligent selection module, and the work order processing collaboration adjustment module are connected to a core processor through a 5G network, and when the order is placed or the processing personnel changes, real-time relationship data is stored in the internal hard disk.

[0027] Compared with the prior art, the application has the beneficial effects that: on the one hand, from the perspective of personnel resource optimization, through deep analysis of historical work data of processing personnel, the ability characteristics and success rate of each personnel in processing different types of work orders are accurately grasped, and then combined with the idle time, the work order is intelligently distributed to the execution personnel with the highest adaptation degree, and the cooperative personnel who are good at processing the weak links of the execution personnel are matched. This way avoids the waste of resources caused by random or experience-based distribution in the past, so that each processing personnel can play to their strengths in the most suitable field, realize efficient use of human resources, and improve the overall work efficiency of the team.

[0028] On the one hand, in terms of work order processing efficiency and quality assurance, the method changes the problems of inefficiency and mistakes that are prone to occur in traditional manual distribution or simple rule distribution. Since the selection of execution personnel and cooperative personnel is based on objective and scientific analysis, problems encountered during work order processing can be supported by personnel skilled in the field in a timely manner, greatly reducing the work order processing time and error probability, ensuring that the work order can be completed quickly and with high quality, and effectively improving customer satisfaction and enterprise service reputation.

[0029] On the other hand, when the execution personnel and the cooperative personnel encounter difficulties during processing, the system can also automatically select the personnel with the highest average processing success rate from the idle personnel as the assisting personnel. This dynamic and flexible cooperation mechanism makes the entire work order processing system more resilient and adaptable, and can cope with complex and variable work scenarios, ensuring the stable and efficient operation of enterprise business, and helping enterprises gain an advantage in the competitive market environment. BRIEF DESCRIPTION OF DRAWINGS

[0030] The accompanying drawings are used to provide a further understanding of the application, and constitute a part of the specification, together with the embodiments of the application, to explain the application, and do not constitute a limitation on the application. In the drawings:

[0031] Figure 1 is a structural diagram of an artificial intelligence-based work order automatic processing system of the application;

[0032] Figure 2 is a flowchart of an artificial intelligence-based work order automatic processing method of the application. DETAILED DESCRIPTION

[0033] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only a part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application.

[0034] Please refer to Figure 1 andFigure 2 The present invention provides a technical solution: an artificial intelligence-based automatic work order processing method, comprising the following steps:

[0035] S1. Based on historical data, analyze the historical processing data of the processing personnel and indicate the current status of the processing personnel;

[0036] S2. When adding a work order, filter the work orders containing keywords and analyze the suitability of the processing personnel for the work order;

[0037] S3. Considering the compatibility and the success rate of the work order, select the executor and coordinator for the work order;

[0038] S4. Adjust the labels of the executor and cooperating personnel, and select the assisting personnel to complete the work order based on the work order information.

[0039] In step S1, after authorization, the processing personnel information is collected, and the processing personnel set is {A1, A2, ..., A i ,…,A I}, for processing personnel A i Perform analysis and process personnel A i The number of times the preset X keywords are processed is {B1, B2, ..., B x ,…,B X}, where B x Indicates processing personnel A i Number of times the work order containing the xth keyword was processed by processing person A i The success rate of processing work orders containing the xth keyword is W i_x , and then get the processing personnel A i The comprehensive treatment success rate W i , W i For processing personnel A i For the average processing success rate of the work order, we substitute i=1,2,…,I one by one to get the comprehensive processing success rate of I processing personnel {W1,W2,…,W i ,…,W I} to the processing personnel, the annotation being the idle time length of the processing personnel, and if the processing personnel is not in an idle state, setting the idle time length to 0; by collecting and analyzing the processing personnel information, the processing capacity of each personnel for different types of work orders can be comprehensively understood, and the strong field and processing level of each personnel can be clearly mastered. The analysis of the processing times and success rates can accurately locate the advantages of the personnel, facilitate the optimization of task allocation, and improve the work order processing efficiency and success rate. Adding the idle time length annotation to the processing personnel can intuitively reflect the working state of the personnel, facilitate the reasonable arrangement of the work load, avoid overwork or resource idling, and realize the scientific regulation of the working rhythm of the personnel. This series of operations can help the manager to master the comprehensive situation of the personnel in real time, improve the scientific nature and pertinence of the management, promote the balanced allocation of personnel resources, enhance the team cooperation efficiency, create an efficient and orderly working environment, promote the overall work efficiency, guarantee the stability of the service quality, and provide strong support for the orderly development of the business and the team development.

[0040] In step S2, when adding a work order, after authorization, the work order information is collected, and the work order keywords are obtained by comparing the preset X keywords, the work order keywords representing the keywords contained in the work order, the work order keywords including {C1, C2, …, C y ,…,C Y}, wherein Y represents the number of keywords included in the work order, C y represents the yth keyword involved in the work order, the processing success rate D i of the personnel A i_y for the work order related to the yth keyword is obtained, and then the adaptation degree E i of the personnel A i for the work order is obtained.

[0041]

[0042] wherein k i1 represents the keyword weight to be calculated, and k i2 represents the comprehensive weight to be calculated.

[0043] The idle time length F i of the personnel A i is considered, the keyword weight k i1 is set, k i1 =f i / f0, wherein f i is the effective idle time length of the personnel A i , f0 is the maximum effective idle time length, when f i ≤f0, f i =F i ; when f i >f0, f i =f0, and the comprehensive weight k i2= k i1 , and then obtain the adaptation degree of the I processing personnel to the work order {E1, E2, …, E i , …, E I}; from the aspects of accurate matching and processing efficiency improvement, the method can accurately obtain the key words of the work order by collecting the work order information and comparing the preset key words, and then calculate the adaptation degree by combining the processing success rate of the processing personnel to the work order related to each key word, so as to ensure that the work order is distributed to the personnel with high processing success rate in the key word field. This makes the processing personnel quickly take over the familiar business, reduces the time waste and processing errors caused by unfamiliar business, greatly improves the efficiency and pertinence of work order processing, and enables the work order to be professionally processed in the shortest time. In terms of optimal allocation of processing resources, the key word weight is set by fully considering the effective idle time of the processing personnel. When the effective idle time of the processing personnel does not exceed the maximum effective idle time, the weight is directly calculated based on the actual effective idle time; otherwise, the maximum effective idle time is used as the reference. Such design avoids the situation of over-reliance or neglect of a certain processing personnel. By dynamically adjusting the key word weight, the workload of the processing personnel is balanced, so that the personnel with longer idle time have more opportunities to undertake work orders, and the overburden of busy personnel is avoided, thereby realizing the reasonable allocation of processing resources and improving the cooperation efficiency of the overall processing team. From the perspective of processing quality and customer satisfaction, the personnel with high processing success rate can process the work order related to the key word more professionally and efficiently, which can improve the quality and accuracy of work order solution and reduce the situation of rework and error processing. The customer's problem can be quickly and effectively solved, which will inevitably improve the customer's satisfaction with the service and enhance the customer's trust in the system and the service team.

[0044] In addition, the method has good dynamic adaptability and flexibility. The key word weight is adjusted in real time according to the effective idle time of the processing personnel, which can timely respond to the changes in the working state of the processing personnel, so that the adaptation degree calculation is more in line with the actual situation, and the system can maintain efficient operation in different working scenarios, thereby providing strong support for the stability and optimization of the work order processing system.

[0045] In step S3, the I processing personnel are sorted in descending order of the adaptation degree to the work order, wherein the adaptation degree of the pth processing personnel to the work order is the highest, and the adaptation degree of the pth processing personnel to the work order is E p , and the pth processing personnel is taken as the executor of the work order;

[0046] The processing success rate of the pth processing personnel to the Y key word related work orders is {D p_1 ,D p_2 ,…,D p_y ,…,D p_Y}, and the average processing success rate of the processing personnel to the Y key word related work orders is {D1, D2, …, D y..., D Y}, wherein D y is the average processing success rate of the yth keyword-related work order by the processing personnel, if D p_y < D y , the yth keyword is classified as a processing keyword, and the set of processing keywords is {H1, H2,..., H p ..., H P}, wherein P represents the number of processing keywords, H p represents the pth processing keyword, a virtual work order is established, the virtual work order contains P processing keywords, and the adaptation degrees of the I processing personnel to the virtual work order {e1, e2,..., e i ..., e I} are obtained, and the processing personnel with the highest adaptation degree to the virtual work order is selected as the cooperating processing personnel;

[0047] The idle time of the cooperating processing personnel is checked, if the idle time of the cooperating processing personnel is 0, the cooperating processing personnel is reselected from the non-cooperating processing personnel until the idle time of the cooperating processing personnel is not 0;

[0048] The idle time of the cooperating processing personnel is checked, if the idle time of the cooperating processing personnel is 0, the processing personnel with the highest processing success rate is reselected from the non-cooperating processing personnel as the cooperating processing personnel until the idle time of the cooperating processing personnel is not 0;

[0049] The adaptation degrees are sorted to precisely match the work order with the main execution personnel, which can ensure that the task is assigned to the personnel who is best at processing the type of work order, maximizes the expertise of the personnel, and improves the initial efficiency and success rate of work order processing. For the weak keyword field of the main execution personnel, the personnel with the strongest processing ability in the field is selected as the assistant, which can effectively make up for the shortcomings of the main execution personnel, form a complementary cooperative working mode, and further guarantee the overall quality of work order processing. At the same time, by checking the idle time of the cooperating personnel, the selection can be dynamically adjusted to avoid the delay or quality decline caused by assigning tasks to busy personnel, ensure that the cooperating personnel has sufficient energy to work, and realize the reasonable allocation of human resources and the scientific balance of task load. This allocation mechanism, which combines main and auxiliary personnel and takes into account the state of the personnel, can not only improve the processing efficiency of individual work orders, but also promote the cooperation between team members, and promote the efficient operation of the overall work process and the stable improvement of service level.

[0050] In step S4, after the execution personnel and the cooperative personnel selection is completed, the work order information is transmitted to the execution personnel and the cooperative personnel, the idle time length of the execution personnel and the cooperative personnel is locked to 0 until the work order is completed, and if the execution personnel and the cooperative personnel submit a help application during the execution of the work order, the processing personnel with the highest average processing success rate of the work order is selected as the assisting personnel from the processing personnel with the idle time length not being 0, the work order information is transmitted to the assisting personnel, and the assisting instruction is issued;

[0051] After the execution and the cooperative personnel selection are completed, the idle time length is locked, which can ensure that the personnel concentrate during the work order processing, avoid processing interruption caused by task switching or resource occupation, guarantee the continuity and concentration of the work order execution, and improve the processing efficiency and quality stability. When the help mechanism is triggered during the execution, the assisting personnel with the highest average processing success rate is selected from the idle personnel, which can quickly respond to complex problems, solve the difficulties in time by means of the personnel with strong professional ability and ready state, and prevent the problems from affecting the overall progress. The mechanism combining the locking and the dynamic help can realize the scientific management of the personnel working state, build a flexible and efficient cooperation network, enable the team to quickly allocate resources when facing different difficulty tasks, form a multi-level support system, enhance the overall ability to cope with complex work orders, promote the experience complementation and cooperation among personnel, create an efficient mutual assistance working atmosphere, and promote the smooth operation of the business process and the continuous improvement of the service efficiency.

[0052] An artificial intelligence-based work order automatic processing system, comprising: a processing personnel state analysis module, a work order keyword adaptive analysis module, a processing personnel intelligent selection module, and a work order processing cooperation adjustment module;

[0053] The processing personnel state analysis module is used for analyzing the historical processing data of the processing personnel based on historical data, and marking the current state of the processing personnel;

[0054] The work order keyword adaptive analysis module is used for screening the keywords contained in the work order when adding the work order, and analyzing the adaptive degree of the processing personnel to the work order;

[0055] The processing personnel intelligent selection module is used for comprehensively considering the adaptive degree and the processing success rate of the work order to select the execution personnel and the cooperative personnel for the work order;

[0056] The work order processing cooperation adjustment module is used for adjusting the label of the execution personnel and the cooperative personnel, and selecting the assisting personnel to complete the work order according to the work order information.

[0057] Embodiment 1: First, the information of the processing personnel is comprehensively collected, the number and success of each personnel processing various types of work orders are counted, the average success rate is calculated to measure the comprehensive processing ability, and the current idle time of the personnel is marked to clearly understand the personnel's strong field and working state for different types of work orders, thereby providing basic data support for task allocation.

[0058] When a new work order is added, the system automatically extracts the keywords in the core content of the work order and identifies the type of the work order. Then, the historical data of the processing personnel are compared and analyzed to evaluate the adaptation degree of each personnel to the type of work order. The adaptation evaluation not only refers to the success rate of the personnel in processing work orders containing the same keywords in the past, but also dynamically adjusts the weight according to the current idle time of the personnel. The personnel with longer idle time have higher priority in matching, ensuring balanced use of human resources and avoiding overloading of busy personnel or idling of idle personnel resources.

[0059] After the adaptation degree is calculated, the processing personnel are sorted in descending order of matching degree, and the personnel with the highest adaptation degree are selected as the main execution personnel to ensure that the work order is led by the personnel who are best at this type of task. Then, the weak links of the main execution personnel in the keywords involved in the work order are analyzed, and the personnel with the highest success rate in processing the weak field and currently in idle state are selected from other personnel as cooperative personnel to form a complementary combination, thereby making up for the shortcomings of the main execution personnel.

[0060] After the work order is allocated, the system automatically locks the idle time of the main execution personnel and the cooperative personnel until the work order is completed, ensuring that the personnel focus on the current task. If a complex problem is encountered during processing, the main execution personnel submits a help application, and the system immediately selects the personnel with the highest comprehensive processing success rate from the personnel with non-zero idle time as an assisting personnel to quickly respond and provide professional support, ensuring smooth progress of the work order processing process. Through this whole set of mechanism, the team realizes precise matching of work orders and personnel capabilities, dynamic balance of work load, and multi-role collaborative work, significantly improving the efficiency and quality of work order processing, and promoting the optimization of the overall efficiency of the team.

[0061] It is apparent for those skilled in the art that the present application is not limited to the details of the foregoing exemplary embodiments, but can be implemented in other concrete forms without departing from the spirit or essential characteristics of the present application. Therefore, the embodiments should be considered in all respects as illustrative and not restrictive, and the scope of the present application is defined by the appended claims rather than the foregoing description, and it is intended to embrace all changes and modifications that fall within the meaning and scope of equivalents of the claims. Any reference signs in the claims should not be considered as limiting the claims involved.

Claims

1. An artificial intelligence-based automatic work order processing method, characterized by: The method comprises the following steps: S1. Based on historical data, analyze the historical processing data of the processing personnel and indicate the current status of the processing personnel; S2. When adding a work order, filter the work orders containing keywords and analyze the suitability of the processing personnel for the work order; S3. Considering the compatibility and the success rate of the work order, select the executor and coordinator for the work order; S4. Adjust the labels of the executor and cooperating personnel, and select the assisting personnel to complete the work order based on the work order information.

2. The method for automatically processing work orders based on artificial intelligence according to claim 1, characterized in that: In step S1, after authorization, the processing personnel information is collected, and the processing personnel set is {A1, A2, ..., A i ,…,A I }, for processing personnel A i Perform analysis and process personnel A i The number of times the preset X keywords are processed is {B1, B2, ..., B x ,…,B X }, where B x Indicates processing personnel A i Number of times the work order containing the xth keyword was processed by processing person A i The success rate of processing work orders containing the xth keyword is W i_x , and then get the processing personnel A i The comprehensive treatment success rate W i , W i For processing personnel A i For the average processing success rate of the work order, we substitute i=1,2,…,I one by one to get the comprehensive processing success rate of I processing personnel {W1,W2,…,W i ,…,W I }, add a label to the processing personnel, labeling it as the idle time of the processing personnel. If the processing personnel is not idle, the idle time is set to 0.

3. The method for automatic work order processing based on artificial intelligence according to claim 2, characterized in that: In step S2, when adding a work order, after authorization, the work order information is collected and compared with the preset X keywords to obtain the work order keywords. The work order keywords represent the keywords contained in the work order. The work order keywords include {C1, C2, ..., C y ,…,C Y }, where Y represents the number of keywords included in the work order, C y Indicates the yth keyword involved in the work order, and gets the processing person A i The success rate of handling work orders related to the yth keyword D i_y , and then get the processing personnel A i Adaptability to work orders E i : where k i1 Indicates the keyword weight to be calculated, k i2 Indicates the comprehensive weight to be calculated.

4. The method for automatically processing work orders based on artificial intelligence according to claim 3, characterized in that: Consider Processor A i Idle time F i Set keyword weight k i1 , k i1 =f i / f0, where f i For processing personnel A i The effective idle time length, f0 is the maximum effective idle time length, when f i When ≤f0, let f i =F i When f i >f0, let f i =f0, comprehensive weight k i2 =k i1 , and then get the adaptability of I processing personnel to the work order {E1, E2, ..., E i ,…,E I }.

5. The method for automatically processing work orders based on artificial intelligence according to claim 4, characterized in that: In step S3, the I processing personnel are sorted from high to low according to their adaptability to the work order, among which the pth processing personnel has the highest adaptability to the work order. The adaptability of the pth processing personnel to the work order is E p , the pth processing personnel will be the executor of the work order.

6. The method for automatic work order processing based on artificial intelligence according to claim 5, characterized in that: The success rate of the p-th processing personnel for Y keyword-related work orders is {D p_1 ,D p_2 ,…,D p_y ,…,D p_Y }, according to historical data, the average success rate of processing personnel for Y keyword-related work orders is {D1, D2, ..., D y ,…,D Y }, where D y is the average success rate of the personnel in handling the work orders related to the yth keyword, if D p_y <D y , then the yth keyword is classified as a keyword to be processed, and the set of keywords to be processed is {H1,H2,…,H p ,…,H P }, where P represents the number of keywords to be processed, H p Indicates the pth keyword to be processed, establishes a virtual work order, and the virtual work order contains P keywords to be processed, and then obtains the adaptability of I processing personnel to the virtual work order {e1, e2, ..., e i ,…,e I }, and then select the processing personnel with the highest adaptability to the virtual work order as the coordinating processing personnel; Check the idle time of the cooperating personnel. If the idle time of the cooperating personnel is 0, reselect cooperating personnel from non-cooperating personnel until the idle time of the cooperating personnel is not 0.

7. The method for automatically processing work orders based on artificial intelligence according to claim 6, characterized in that: In step S4, after the executor and the cooperating processing personnel have completed their selection, the work order information will be transmitted to them, and the idle time of the executor and the cooperating processing personnel will be locked to 0 until the work order is completed. If the executor and the cooperating processing personnel submit a request for help during the execution of the work order, then among the processing personnel whose idle time is not 0, the processing personnel with the highest average work order processing success rate will be selected as the assisting personnel, and the work order information will be transmitted to the assisting personnel and assistance instructions will be issued.

8. An artificial intelligence-based automatic work order processing system, the system being applied to the artificial intelligence-based automatic work order processing method according to any one of claims 1 to 7, characterized in that: The system includes: a processing personnel status analysis module, a work order keyword adaptation analysis module, a processing personnel intelligent matching module and a work order processing collaborative adjustment module; The processing personnel status analysis module is used to analyze the historical processing data of the processing personnel based on historical data and indicate the current status of the processing personnel; The work order keyword adaptation analysis module is used to screen the work orders containing keywords when adding work orders and analyze the suitability of the processing personnel for the work orders; The intelligent selection module for processing personnel is used to comprehensively consider the adaptability and the success rate of processing the work order, and select the execution personnel and the cooperating processing personnel for the work order; The work order processing collaboration adjustment module is used to adjust the labels of the execution personnel and the cooperating processing personnel, and select the assisting personnel to complete the work order according to the work order information.

9. The artificial intelligence-based automatic work order processing system according to claim 8, characterized in that: The processing personnel status analysis module, work order keyword adaptation analysis module, processing personnel intelligent matching module and work order processing collaborative adjustment module are connected to the core processor through the 5G network. When the order or processing personnel changes, real-time relation data is stored on the internal hard disk.

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